| 000 | 03530nam a22005775i 4500 | ||
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| 001 | 978-981-97-5323-9 | ||
| 003 | DE-He213 | ||
| 005 | 20251030112906.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240822s2024 si | s |||| 0|eng d | ||
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_a9789819753239 _9978-981-97-5323-9 |
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| 024 | 7 |
_a10.1007/978-981-97-5323-9 _2doi |
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| 050 | 4 | _aT57.6-.97 | |
| 072 | 7 |
_aKJT _2bicssc |
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_aKJMD _2bicssc |
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_aBUS049000 _2bisacsh |
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_aKJT _2thema |
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_aKJMD _2thema |
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| 100 | 1 |
_aXie, Naiming. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _982735 |
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| 245 | 1 | 0 |
_aGrey Forecasting _h[electronic resource] : _bMechanism, Models and Applications / _cby Naiming Xie, Baolei Wei. |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2024. |
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| 300 |
_aXIII, 200 p. 24 illus., 15 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSeries on Grey System, _x2731-4944 |
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| 505 | 0 | _a1. Introduction -- 2. Architecture of grey forecasting models -- 3. Mechanism and reduction of grey forecasting models -- 4. Continuous-time grey endogenous forecasting models -- 5. Discrete-time grey endogenous forecasting models -- 6. Continuous-time grey exogenous forecasting models -- 7. Discrete-time grey exogenous forecasting models -- 8. Nonlinear grey forecasting models -- 9. Grey number-oriented forecasting models -- 10. Comments and future thinking. | |
| 520 | _aThis book aims to present an overview of grey system models for time series modelling and forecasting. It is about modelling and forecasting time series with ordinary differential equations, especially when the available samples are extremely limited. Grey system models (GSM) develop sequence operators to nonparametrically identify the underlying dynamics from the limited observations. This book concerns about two important modelling themes, small sample and poor information. The former focuses on the mechanism and methodology of GSMs for small-sample real-number time series, and the latter on the uncertainty quantification of grey number together with its small-sample modelling principles. In this book, a broad entry point to applied data science for students majoring in economic, management science, and engineering is applied, covering a wide range of topics from basic introductory material up to research-level techniques. | ||
| 650 | 0 |
_aOperations research. _957943 |
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| 650 | 0 |
_aMathematics _xPhilosophy. _969649 |
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| 650 | 0 |
_aEconometrics. _957695 |
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| 650 | 1 | 4 |
_aOperations Research and Decision Theory. _967143 |
| 650 | 2 | 4 |
_aPhilosophy of Mathematics. _969650 |
| 650 | 2 | 4 |
_aQuantitative Economics. _970330 |
| 700 | 1 |
_aWei, Baolei. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _982736 |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819753222 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819753246 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819753253 |
| 830 | 0 |
_aSeries on Grey System, _x2731-4944 _977168 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-97-5323-9 |
| 912 | _aZDB-2-BUM | ||
| 912 | _aZDB-2-SXBM | ||
| 999 |
_c62655 _d62655 |
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